Comparative analysis of the postadmission and antemortem oropharyngeal and rectal swab microbiota of ICU patients.

Shotgun metabarcoding was conducted to examine the microbiota in a total of 48 samples from 12 critically ill patients, analyzing samples from both the oropharynx and rectum. We aimed to compare their postadmission microbiota, characterized as moderately dysbiotic, with the severely dysbiotic antemortem microbiota associated with patients' deaths. We found that, compared with postadmission samples, patient antemortem swab samples presented moderate but not significantly decreased diversity indices.

Self-Reported Learning Strategies and Preferences in Health Informatics.

Despite the proliferation of educational programmes in Health Informatics (HI) worldwide, there is limited knowledge regarding students' preferences and learning strategies in HI courses. To address this gap, we conducted a study to gather and analyse data from three HI courses. Employing the Motivated Strategies for Learning Questionnaire (MSLQ) and theories of deep and surface learning, we designed a questionnaire to collect data.

Education Challenges Among Early Career Researchers in Medical Informatics.

There is limited knowledge about early career researchers' challenges when studying the interdisciplinary field of Medical Informatics (MI). We conducted a qualitative content analysis through semi-structured interviews with early career researchers in MI, including individuals pursuing Master's, PhD, and postdoctoral research programmes, across two higher education institutions in the UK. We identified five challenges, including understanding biological jargon, interpreting biological data, interdisciplinary communication, understanding mathematical/statistical concepts, and programming difficulties.

Providing insights into health data science education through artificial intelligence.

Background: Health Data Science (HDS) is a novel interdisciplinary field that integrates biological, clinical, and computational sciences with the aim of analysing clinical and biological data through the utilisation of computational methods. Training healthcare specialists who are knowledgeable in both health and data sciences is highly required, important, and challenging. Therefore, it is essential to analyse students' learning experiences through artificial intelligence techniques in order to provide both teachers and learners with insights about effective learning strategies and to improve existing HDS course designs.

Recurrence Patterns after Radiotherapy for Glioblastoma with [(11)C]methionine Positron Emission Tomography-Guided Irradiation for Target Volume Optimization.

C methionine (C-MET) is increasingly being used in addition to contrast-enhanced MRI to plan for radiotherapy of patients with glioblastomas. This study aimed to assess the recurrence pattern quantitatively. Glioblastoma patients undergoing 11C-MET PET examination before primary radiotherapy from 2018 to 2023 were included in the analysis.